Sub-micron spin-based magnetic field imaging with an organic light emitting diode

Quantum sensing and imaging of magnetic fields has attracted broad interests due to its potential for high sensitivity and spatial resolution. Common systems used for quantum sensing require either optical excitation (e.g., nitrogen-vacancy centres in diamond, atomic vapor magnetometers), or cryogenic temperatures (e.g., SQUIDs, superconducting qubits), which pose challenges for chip-scale integration and commercial scalability. Here, we demonstrate an integrated organic light emitting diode (OLED) based solid-state sensor for magnetic field imaging, which employs spatially resolved magnetic resonance to provide a robust mapping of magnetic fields. By considering the monolithic OLED as an array of individual virtual sensors, we achieve sub-micron magnetic field mapping with field sensitivity of ~160 µT Hz−1/2 µm−2. Our work demonstrates a chip-scale OLED-based laser free magnetic field sensor and an approach to magnetic field mapping built on a commercially relevant and manufacturable technology.

The prepatterned ITO/glass substrates are purchased from Kintec Company (Hong Kong). The ITO substrates are cleaned by standard cleaning procedure and dried out in the vacuum drying oven at 120 °C overnight before usage. The glass substrate dimension is: 30.0 (±0.05) mm × 20.0 (±0.05) mm × 0.7 (±0.01) mm. We note that shadow mask, which will be used for thermal deposition of the top Al electrode of OLED, is precisely cut by laser based on the substrate dimension. The precision of the shadow mask dimension is particularly important for the good alignment between the substrate and the shadow mask, which is the key step in the later OLED fabrication process (see Supplementary Fig. 2).
The photoresist structures for the two insulating layers and the microwave resonator layer are prepared through the standard photolithography process using MA6 system, using negative photoresist nLOF2020 and developer ZA826MIF with optimized parameters. The details of the photolithography steps are as following: 1) Spin nLOF2020 on the substrate at 3000 RPM for 30 s, resulting in photoresist layer thickness of ~2.3 µm 2) Prebake the photoresist at 115 °C for 1 min 3) UV exposure for 4.5 s 4) Post exposure bake (PEB) the photoresist at 115 °C for 1 min 5) Develop in AZ826MIF for 1 min 6) DI water rinse for 20 s, and nitrogen gun dry 7) Further bake at 115 °C for 2 mins to remove any water residue 8) Post plasma cleaning for 10 mins (plasma etching rate ~ 30 nm / per min) Here we choose Al2O3 as the insulating material because of its excellent electrical isolation property, more importantly, its compatibility with the materials and fabrication methods that are used in this work. The breakdown field of Al2O3 by ALD at room temperature is about 8 MV/cm (or 0.8V/nm), so 45 nm thickness is thick enough for OLEDs, whose operational voltage is in range of 0 V-15 V. The ALD system is CNT Savannah S200. The precursors for Al2O3 in ALD are water vapor (H2O) and Trimethylaluminum (TMA). The chamber temperature for the ALD process is set at 120 °C. We note that the chamber temperature cannot be set too high as it would solidate the photoresist and the following liftoff process will become exceedingly difficult. The temperature in principle can be lower such as 80 °C, which will ease the following lift-off process, but the cycle time will increase, and the total deposition time will increase dramatically. There is a trade-off between the deposition temperature and deposition time cost. The total deposition time for 45 nm Al2O3 by ALD at 120 °C is about 9.5 hours.
Following up the ALD, the lift-off procedure of Al2O3 is carried out by immersing the samples in the N-Methyl-2-pyrrolidone (NMP) bath. To allow the NMP to penetrate the conformal insulating layer and attack the photoresist below quicker, it is necessary to scratch the surface of sample manually and slightly at locations without pattern features. For the bottom insulating layer, we could easily scratch the surface close to the edge of the substrate as there is no patterns underneath; while for the top insulating layer, we employ a Cascade probe station and use the sharp metal probe-tip to crack the photoresist pillar inside the resonator gently top downwards. After the scratch, samples are immerged in the NMP bath on hotplate at 100 °C in a fume cupboard, until the lift-off procedure is completed.
For the resonator layer deposition, the substrates with prepatterned photoresist structure are transferred to a thermal evaporation chamber (Jurt J. Lesker) for the metal deposition. The vacuum condition is of ~10 -6 mbar, and the layers stack is Ti (10 nm) / Au (500 nm) / Ti (10nm).
The first 10 nm Ti layer is deposited as adhesion layer for the following Au deposition onto the glass surface. For the Au layer deposition, the first 100 nm is deposited with a low rate of 0.5 A/s, to minimize the heating effects on the prepatterned photoresist structure, such as deforming or softening; the next 400 nm is deposited with a high rate of 2 A/s for time saving. The second 10 nm Ti layer is deposited as another adhesion layer for the spin-coating photoresist in the following photolithography procedure. Standard lift-off is followed in the NMP bath at 100 °C. Figure 2: sketch of the device fabrication (a) where a micron-size OLED is fabricated inside the active area ( ~ 80 µm) and (b) the top Al electrode is deposited by using a well aligned shadow mask. (c) Photograph of the PCB platform for the device mounting and electrical connection. The device is mounted onto the PCB via a 3D printed plastic lid. The device is electrically connected to the PCB via pogo pins (both AC for the resonator and DC for the OLED). The OLED is encapsulated by using a square glass coverslip (10 mm × 10 mm) with a cavity (300 µm depth) in it to avoid physical contact with the top Al electrode. (d) Photograph of the device under operation. Profiles of the bottom ITO electrode, the top Al electrode, and the Au resonator are highlighted using dashed lines. There is a small offset of the top Al electrode from the centre, which is due to the manual alignment of the shadow mask through the OLED fabrication procedure. The scale bar in (d) is 100 µm.

Supplementary Method 2: Background noise and RF power broadening
There is a "wobbling" feature noise in the raw magnetic resonant spectrum with sweeping the microwave frequency. We suspect that the noise origins from the microwave component in the experimental setup as we see similar "wobbling" feature in the S11 curve of the SMA cable, which might be due to the mismatch of 50 Ω impedance of the RF output, resulting in some end-reflection of the signal in the cable. Such noise is then transmitted and modified through the PCB and the resonator, and eventually coupled to the OLED, resulting in those "wobbling" feature noise in the final EDMR spectrum ( Supplementary Fig. 4) contributing to the overall background noise. In addition, the amplitude of the noise is not a constant, but varies at different microwave frequency ( Supplementary Fig. 3). Such baseline noise can be measured separately and then subtracted from the raw experimental data ( Supplementary Fig. 4). We note that such impedance mismatch and relevant noises due to possible electrical coupling between the RF source and the OLED could be potentially minimized by optimizing the device architecture, such as the geometry of the resonator and the spatial distance and relative orientation between the resonator and the OLED. Figure 3: S11 curve of (a) SMA cable itself, which is connected to the microwave source directly, and (b) the microwave resonator connected to the microwave source through the PCB, showing a resonant frequency around 900 MHz.

Supplementary Figure 4: Raw signal and background noise in (a) X-channel and (b) Y-channel of the lock-in detection where the microwave frequency is swept. The EDMR signal in (c) X-channel and (d)
Y-channel after the background noise is subtracted. The final EDMR signal is given by ∆ = √(∆ ) 2 + (∆ ) 2 with negative sign 2,3 .
We also investigate the effect of the RF power broadening on the magnetic resonance spectrum. Supplementary Fig. 5(a) shows that the EDMR signal (signal sign is negative) amplitude monotonically increases when the RF power increases (equivalently 1 field strength increases). This is consistent with previously literature reports 3 , confirming that the RF power (~5 dBm) used in the experiment is indeed in the low RF driving power regime ( 1 << hyp ). In this low driving power regime, the power broadening effect is negligible, and the magnetic resonant spectrum (both EDMR and ODMR) can be decoupled into two Gaussian functions with equal -factor of ~2.0026. In addition, all the EDMR spectrums with different RF power are well fit using two Gaussian functions and more importantly the center of the peak remains the same position, indicating that the effect of RF power on field detection accuracy is also negligible.

Supplementary Method 3: Angle dependent EDMR
To verify that the magnetic resonance condition is independent of the orientation of the external magnetic field 0 in our device, a separate angle dependent EDMR measurement is carried out. As sketched in Supplementary Fig. 6(a), the device is mounted on a rotation stage sitting between two electromagnet poles. Instead of changing the orientation of the field B0, the orientation of microwave field 1 is changed equivalently. When the device rotates, the orientation of the microwave field B1 rotates in the horizontal − plane, labelled by angle as shown in Supplementary Fig. 6(b). We find that: (1) the amplitude of the EDMR spectrum peak, which corresponds to the maximum change of the EDMR signal, is proportional to the projection of the 1 field along the orthogonal direction of 0 , and the relationship between the amplitude and the rotation angle can be well fit by a sine wave function; (2) the resonant frequency of the EDMR spectrum peak ( ), which corresponds to the external magnetic field 0 ( = 0 , ), remains the same with 99.94% confidence. We also observed an exceedingly small EDMR signal at = 90° and = 270°, which is attributed to the spatial variation of the microwave field. The distance between the microwave resonator and the OLED is much smaller than the wavelength of the microwave radiation, hence the OLED is in the near-field region of the 1 field. As a result, the spatial orientation of the 1 field is determined by the dimensions of the resonator itself and the surrounding conductors, and the orientation varies slightly in the OLED region. Therefore, there is always a small in-plane projection (B1//) of 1 field during the whole rotation, and it plays a dominant role in the non-zero EMDR spectrums at = 90° and = 270°.
The small variation of resonant B0 field value origins from the following aspects: (1) The influence of the SMA connectors on the PCB. We find that those SMA connectors used in this work show weak paramagnetic behaviour under large external magnetic field, and it leads to a very weak disturbance on the Gauss probe reading during the rotation. The disturbance becomes noticeable (at 0.1 mT scale) at some angles (60° to 120°) where the SMA connectors are closest to the Gauss probe. We note that such disturbance has been removed in Supplementary Fig. 6(d) through an independent and careful calibration process. (2) The finite step size of the sweeping magnetic field, which results in an uncertainty of the 0 value extraction. (3) The uniformity of the static magnetic field 0 between the two electromagnet poles. The uniformity of the field depends on the dimensions of the two poles, the gap between them, and the spatial location. In practice, the magnetic field detected by the Gauss probe is always slightly different from the actual field the device experiences, and such difference may even vary during the rotation as the rotation setup is not perfectly aligned with the magnet. Comparison of the simulated magnetic field and the experimentally measured field using Gauss probe. The strength of the magnetic field here is a function of the movement distance along the -direction from the top surface of the magnet. We note that the total thickness of the Hall probe is about 1.6 mm, therefore the starting position for the Hall probe measurement is about 0.8 mm (half of the probe thickness) as labelled out by the dash line, where we positioned the probe right adjacent to the magnet. The similarity between the Hall probed field and the simulation field is 98.5 %. Comparison of experimentally measured field (grey dots) and the simulated magnetic field (colour curves) with various starting position x0, as a function of the movement distance along x-direction in (c) and along y-direction in (d), respectively. We note that the − coordinates in (c) and (d) is a local frame within the 2D map plane, which is labelled out separately in (a). Similarity between the measured field and the simulation field is 99.8 % ( 0 = 0.2 mm) in (c), and 98.6 % ( 0 = 0.4 mm) in (d). The similarity calculation formula is listed as below. We note that the parameters of diameter, length and material property are obtained directly from the product datasheet, and the edge radius is estimated based on our own measurements. The edge radius here refers to the smooth curvature of the surface edge of the magnet cylinder. In addition, the influence of the edge radius on the simulation field distribution is investigated by comparing simulation with edge radius 0.2 mm and simulation with edge radius 0.0 mm. We find: (1) for the far-field region ( > 8.0 mm), the difference of the field between two cases, both amplitude and direction, is negligibly small; (2) for the near-field region ( < 5.0 mm around the edge area), the difference is still quite small but not negligible. Therefore, in the Main Fig. 2 where the distance > 10 mm, simulation field remains the same regardless the estimated value of the edge radius.

Diameter (mm) Length (mm) Edge radius (mm) Materials
• Definition of similarity: • Standard error in the OLED region and diffusion region Figure 9(a) shows the spatial distribution of the standard error (SE) of the resonant peak frequency of the ODMR spectrums. The 2D map demonstrates three distinguishable regions: (1) the central region with R < R2, where the SE is clearly larger than the surrounding regions. The reason of the large SE in this region is because of the electrical coupling between the resonator and the device electrodes. We suspect that the 'wobbling' feature noise from the resonator (see Supplementary Fig. 3) is encoded into the device where an electrical coupling between the ITO and Al electrodes is induced. Such electrical coupling is eventually transmitted to the device output (both current and the EL), reducing the overall SNR.
(2) the ring region with R2 < R < R3, where the SE is the smallest. The EL emission in this ring region is due to the high hole mobility in the PEDOT:PSS layer. In specific, holes are injected from ITO electrode into PEDOT:PSS layer through the defined area (ROLED = 40 µm), then diffuse in the PEDOT:PSS layer along the in-plane direction outwards. Under the bias voltage, these diffusing holes are gradually injected into the emitting layer along the diffusion path, eventually forming excitons through combing with the electrons which are injected from the top Al electrode. As this is the diffusion region, the noise caused by the electrical coupling between the two electrodes is much weaker compared to the central region. Therefore, the SE in this ring region is smaller than the central region.
(3) the edge region with R > R3, where the SE is large compared to ring region though it is also the diffusion region. The reason is because the EL signal is much weaker in this edge region, therefore the over SNR is much smaller. • Magnetic field gradient sensitivity The magnetic field gradient sensitivity is calculated from the uncertainty of the field gradient, which is given by is the measured magnetic field difference between two super-pixels located at 1 x and 2 x , and 21 x x x  = − is the distance between them (refers to the inset in Main Figure 4). Based on the error propagation, the minimum detectable gradient min G  is given as following: is the uncertainty of the magnetic field (or minimum detestable magnetic field difference). Here we assume that uncertainty of the magnetic field is location independent or ideally the same across the whole device, where min x  is the uncertainty of the distance measurement and we assume min x  is location independent as well.
For a digital distance measurement, the minimum uncertainty is equal to the super-pixel width (see the inset in figure 4 in the main content), min xw  = As the whole measurement system is fixed firmly on the optical table, and no relative movement between the camera and device has been observed in a similar setup from our previous work 4 , we believe that the actual uncertainty of the distance measurement caused by vibration and relative displacement is negligibly small compared to w .
By plugging equations (2-4) into equation (1) Equation (7) can be rewritten as below:  is the minimum detectible magnetic field difference (or uncertainty of the magnetic field as mentioned above), and it depends on the super-pixel size w (or binning size ) as shown in Supplementary Figure 11; xw  = is the uncertainty of the distance measurement as shown in equation (4). Equation (8-1) can also be rewritten as equation (8-2)